The rapid rise in electric vehicle (EV) adoption demands innovative thermal management solutions to boost battery performance and passenger comfort. This paper introduces a novel control strategy for simultaneous battery and cabin cooling in EVs, utilizing a two-stage fuzzy logic controller. The proposed system incorporates a detailed plant model to simulate real-world conditions and dynamically optimize compressor speed, ensuring energy-efficient thermal management.
In the first stage, the fuzzy controller sets the initial compressor speed based on primary inputs such as battery and cabin temperatures. The second stage fine-tunes this speed by considering secondary parameters like condenser and chiller pressures, along with the power output ratio from the plant model. This multi-stage approach guarantees efficient cooling for both the battery and cabin while maintaining safe operating conditions.
Our research showcases the efficacy of this control strategy in achieving optimal thermal management in EVs, tackling the challenges of maintaining battery and cabin temperatures under varying ambient conditions. The findings suggest ways to improve energy efficiency and make components last longer, leading to more sustainable and reliable electric transport.